Control Of Synchronous Motor Research Articles

Extreme learning machine‐based super‐twisting integral terminal sliding mode speed control of permanent magnet synchronous motors

AbstractThis article proposes an extreme learning machine (ELM)‐based super‐twisting integral terminal sliding mode control (STITSMC) for speed regulation of a permanent magnet synchronous motor (PMSM). First, the PMSM is modeled in a non‐cascade control structure for fast system response and uncertainty compensation in the speed and torque loops. Second, the STITSMC is designed with integral actions in both the sliding surface and the reaching law to reduce chattering. Third, the ELM is constructed to compensate for the system lumped disturbance, and relax the disturbance upper bound required by the controller which further reduces the chattering. Fourth, the stability of the whole control system is proved based on the Lyapunov method and the finite time convergence regions are derived for both the reaching and the sliding phases. Finally, the comparative simulations and experiments are conducted to show the superiority of the proposed control.

Pseudorandom high‐frequency injection synchronous reluctance motor sensorless control with parameter variation consideration

AbstractThe sensorless control of synchronous reluctance motor (SynRM) in the zero and low‐speed domain using the traditional high‐frequency injection method has the problems of audible noise caused by the high‐frequency injection and high‐frequency loss caused by the change of working conditions, which limits the practical application of SynRM in the industrial field. To solve the problem of high‐frequency noise and loss, a pseudo‐random high‐frequency injection method considering parameter variation is proposed in this paper. Firstly, the signal injection form was adjusted to expand the power spectral density of the high‐frequency current, and the current energy spike was suppressed to reduce high‐frequency noise. Secondly, the current demodulation was combined with the flux map model to complete the injection voltage amplitude adjustment, so that the response current was kept constant under multiple operating conditions to reduce the high‐frequency loss. At the same time, the flux map model is applied to the observer to reduce the rotor position estimation error caused by the cross‐coupling effect. Under the condition of satisfying the dynamic and steady performance requirements of sensorless control, the high‐frequency loss and sharp noise caused by the high‐frequency injection method are effectively suppressed. Finally, experiments were carried out on a 1.5 kW SynRM drive platform to verify the feasibility and effectiveness of the sensorless control scheme in this paper.

Fixed-Time Consensus Multi-Agent-Systems-Based Speed Cooperative Control for Multiple Permanent Magnet Synchronous Motors with Complementary Sliding Mode Control

To improve the tracking performance and robustness of traditional multi-motor speed cooperative control, this paper proposes a speed cooperative control method for multiple permanent magnet synchronous motors (multi-PMSMs) based on the fixed-time consensus protocol for multi-agent systems (MASs) combined with CSMC. Firstly, the speed regulation system of multi-PMSMs is regarded as a MAS. By designing a distributed consensus protocol based on an undirected communication topology, the system achieves fixed-time consensus convergence. Then, a terminal integral sliding mode observer (TISMO) is designed to estimate disturbances, and feedforward compensation is introduced into the consensus protocol to obtain the desired q-axis current. Furthermore, within the framework of the vector control speed cooperative system of PMSMs, a CSMC is designed to track the q-axis reference current. Meanwhile, the stability of the above controllers and observers is theoretically proven using the Lyapunov functions. Finally, comparative experiments are conducted on a multi-PMSM speed regulation experimental platform to verify the proposed control method against the traditional deviation coupling control (DCC) method. The results indicate that under the new control method proposed in this paper, the chattering phenomenon is reduced by about 2 r/min compared to the traditional DCC method. During sudden load and sudden relief load conditions, the speed fluctuation is reduced by approximately 4%, demonstrating good tracking performance and strong robustness.

Active Disturbance Rejection Control for Flux Weakening in Interior Permanent Magnet Synchronous Motor Based on Full Speed Range

To address the impact of load disturbances on the full-speed-range control of an interior permanent magnet synchronous motor (PMSM), an active disturbance rejection control (ADRC) method is proposed. The speed loop employs phased field-weakening control (FW) based on ADRC, while the current loop utilizes proportional-integral-derivative (PID) control. Starting from the motor parameters, the Lagrange multiplier method was used to derive the critical speeds for the maximum torque per ampere (MTPA) and maximum torque per voltage (MTPV) ratios, and the timing for the field-weakening control was analyzed. A full-speed-range control model of the motor was established, and an ADRC-based speed loop controller was designed to achieve smooth transitions between high speeds and anti-disturbance solid capabilities. Based on the proposed control strategy, a 21 kW PMSM was used as the research object, and a full-speed-range control simulation model was developed in MATLAB/SIMULINK to verify the strategy. Compared to the traditional PID control, the simulation results demonstrate that the proposed strategy effectively observes and compensates for load disturbances, significantly reducing initial torque oscillations under three different operating conditions. After a sudden load increase, torque oscillations were reduced by 16%, with the stator current reaching steady state 0.03 s faster, response speed improving by 0.02 s, smooth transitions between speed ranges, and enhanced anti-disturbance performance.

Analysis of Optimization Algorithms Used in Permanent Magnet Synchronous Motor Control According to Different Performance Indices

Permanent magnet synchronous motors (PMSM) can be produced at lower costs with new developments in magnet technology and are widely used in many industrial areas due to their low energy consumption. The widespread use of PMSM brings with it the requirement for high accuracy control performance. In order to achieve high performance accuracy, vector control technique is generally preferred. However, the parameter values of the controllers used in this technique are very important for motor performance. Tuning these parameters by optimization techniques instead of classical methods has become a popular topic. Nowadays, modern control methods show more effective control behavior than classical control methods, which has made the use of modern control methods widespread and studies on modern control methods have intensified. In this study, the analysis of different optimization algorithms used in the control of an PMSM according to their performance indices is investigated in Matlab-Simulink environment. As a result of simulation with different optimization algorithms under the same conditions, the analysis of optimization algorithms using different performance indices such as integral of the absolute value of the error (IAE), integral of the square of the error (ISE), Integral of the Square of the Error Multiplied by Time (ITSE), and Integral of the Absolute Error Multiplied by Time (ITAE) is carried out.

Retraction Note to: Design and performance analysis of adaptive neuro-fuzzy controller for speed control of permanent magnet synchronous motor drive

Retraction Note to: Design and performance analysis of adaptive neuro-fuzzy controller for speed control of permanent magnet synchronous motor drive

Sensorless control of permanent magnet synchronous motor based on two stage low pass filtering sliding mode observer

Sensorless control of permanent magnet synchronous motor based on two stage low pass filtering sliding mode observer

Speed sensorless control of permanent magnet-assisted bearingless synchronous reluctance motor based on enhanced linear extended state observer

Speed sensorless control of permanent magnet-assisted bearingless synchronous reluctance motor based on enhanced linear extended state observer

Research on optimum design and control of permanent magnet synchronous motor for elevator

Abstract Due to the impact of the world energy crisis and environmental pollution problems, the combination of frequency converter and permanent magnet synchronous motor (PMSM) as the core of elevator drive has become a new direction for the development of the elevator industry. Compared with the traditional electric excitation synchronous motor, because the rotor of PMSM adopts permanent magnet excitation, no excitation winding, brush and slip ring are needed, the motor volume is greatly reduced. At the same time, for there is no excitation loss, the efficiency of PMSM) is higher than that of electric excitation synchronous motor. Therefore, the application of PMSM in elevator drive system has more obvious advantages. In this paper, PMSM for elevator is taken as the research object, and motor design software Motor-CAD is used to optimize the design of a kind of PMSM with power level. Then, the fine-tuned and optimized model is imported into the finite element analysis software, and the magnetic field analysis method is used to simulate the electromagnetic field of PMSM, so as to observe the magnetic field distribution of PMSM in the static field. At the same time, the three phase EMF and current waveform of PMSM is analysed to verify the design meets the requirements. Finally, the cogging torque of PMSM is studied in detail. Because the stator fractional slot winding design is adopted, the cogging torque of the prototype is greatly reduced.

Adaptive Current Angle Compensation Control Based on the Difference in Inductance for the Interior PMSM of Vehicles

Achieving good performance in terms of a fast and accurate maximum torque per ampere (MTPA) control method depends on both accurate parameter estimation and a sophisticated control strategy. However, it often requires a complex and long computational process. This paper proposes an efficient control method using the relationship of torque and current angle for maximum torque per ampere control of the interior permanent magnet synchronous motor (IPMSM) for vehicle application. It was found that it is not necessary for the control method to determine the inductance in the d-q axes; the identification of the difference between each axis is enough. Furthermore, this paper presents a simple and effective procedure to estimate the difference in inductance online, where the linear iron loss calculation method is also designed to support the above process. The proposed control method was experimentally validated on a 5 kW prototype by a TMS320F28335 microcontroller and DSPACE synchronized with a personal computer. The results show that the control process has faster and more accurate performance than the conventional method.

Modeling of genetic algorithm tuned adaptive fuzzy fractional order PID speed control of permanent magnet synchronous motor for electric vehicle

This study presents a novel Genetic Algorithm-optimized Adaptive Fuzzy Fractional Order Proportional Integral Derivative (GA-AFFFOPID) controller for enhancing the speed control performance of permanent magnet synchronous motor (PMSM) drives in Electric Vehicles. The proposed GA-AFFFOPID controller, which combines the advantages of genetic algorithm optimization and adaptive fuzzy fractional-order PID control, represents a unique and innovative approach to address the control challenges associated with PMSM drives. Permanent magnet synchronous motor technology, known for its efficiency, compactness, reliability, and versatility in motion control applications, is increasingly adopted in electric vehicle drive systems. However, the inherent non-linearity, dynamics, and uncertainties of permanent magnet synchronous motors pose significant control challenges. The exceptional performance of the GA-AFFFOPID controller, demonstrated through its superior system dynamics, precise speed tracking, and robustness against parameter variations and sudden load disturbances, underscores the significant advancements enabled by the genetic algorithm optimization technique in improving the control performance of PMSM drives for electric vehicle applications. Comparative analysis with traditional control methods demonstrates the exceptional performance of the Genetic Algorithm-optimized Adaptive Fuzzy Fractional Order Proportional Integral Derivative controller. These findings highlight the significant performance improvements facilitated by the genetic algorithm optimization technique in enhancing the control performance of the adaptive fuzzy fractional order PID controller in PMSM drives for electric vehicle applications.

Real-Time Identification and Nonlinear Control of a Permanent-Magnet Synchronous Motor Based on a Physics-Informed Neural Network and Exact Feedback Linearization

This work proposes a novel method for the real-time identification and nonlinear control of a permanent-magnet synchronous motor (PMSM) based on a Physics-Informed Neural Network (PINN) and the exact feedback linearization approach. The proposed approach is presented in a direct-quadrature framework, where the quadrature current and the rotational speed are selected as outputs and the direct and quadrature voltages are selected as inputs. A nonlinear difference equation is selected to describe the physical dynamics of the PMSM, and a PINN is designed based on the aforementioned structure. A simplified training scheme is designed for the PINN based on a least-squares structure to facilitate online training in real time. A nonlinear controller based on exact feedback linearization is designed by considering the nonlinear model of the system identified based on the PINN. Therefore, the proposed approach involves identification and control in real time, where the PINN is trained online. In order to track the reference for the rotational speed, a nonlinear controller with integral action based on exact feedback linearization is designed based on a linear quadratic regulator. As a result, the proposed approach can be used to identify the system to be controlled in real time, and it is able to track any small change in the real model; in addition, it is robust to both external and internal disturbances, such as variations in torque load and resistance. The proposed approach is evaluated through simulation and using a real PMSM, and the results of reference tracking are evaluated under disturbances. The identification performance is evaluated by using a Taylor diagram under closed-loop and open-loop structures, where ARX and NARX structures are used for comparison. It is thereby verified that this novel proposed control approach involving a PINN-based model can adequately track the dynamics of a PMSM system, where the performance of the proposed nonlinear control is maintained even when using the identified model based on the PINN.

Weightless Model Predictive Control for Permanent Magnet Synchronous Motors with Extended State Observer

Traditional model predictive torque control (MPTC) predicts the torque and flux values for the next time step and selects the voltage vector that minimizes the cost function as the optimal vector to apply to the inverter. This control approach is straightforward and allows for multi-objective control, but it has some issues in terms of the dynamic steady-state performance and parameter robustness. Therefore, this paper proposes a weightless model predictive control method based on an extended state observer (ESO). By designing an improved ESO to observe and compensate for motor parameter disturbances in real time, and employing a novel 2-D switching table and voltage vector sector selection diagram, the method evaluates three out of eight voltage vectors based on the torque and stator flux error signals. This reduces the computational load while increasing the number of candidate voltage vectors. Finally, a cost function without weighting factors is designed to lower the computational complexity. The simulation results show that the proposed new control method effectively reduces the torque and flux ripple and improves the current waveform compared to traditional MPTC.

Maximum torque per ampere control of permanent magnet reluctance hybrid rotor dual stator synchronous motor based on sliding mode speed controller

AbstractThis paper proposes a maximum torque per ampere (MTPA) control method for a permanent magnet reluctance hybrid rotor dual stator synchronous motor (PMRHRDSSM) based on a sliding mode speed controller, in response to the complex and special electromagnetic relationship of the motor. The paper focuses on the special electromagnetic relationship of PMRHRDSSM with stator winding series structure. Firstly, the trajectory equation of PMRHRDSSM MTPA stator current vector is derived, and based on the relationship between PMRHRDSSM torque and reluctance dq‐axis current, a PMRHRDSSM current controller that meets MTPA constraints is designed. Afterwards, a PMRHRDSSM sliding mode speed controller was designed with input speed error and output reference torque. Finally, an experimental platform for the proposed control method was established, and the control method was experimentally validated.

Radial Basis Function Neural Network and Feedforward Active Disturbance Rejection Control of Permanent Magnet Synchronous Motor

A composite control strategy is proposed to improve the position-tracking performance and anti-interference capabilities of permanent magnet synchronous motors (PMSMs). This strategy integrates an active disturbance rejection controller (ADRC) and a radial basis function neural network (RBFNN) with feedforward control. Initially, the flexibility and robustness of the ADRC are utilized in the position loop control. Subsequently, the parameters of the extended state observer (ESO) within the ADRC are optimized, benefiting from the fast convergence speed and optimal approximation provided by the RBFNN. To further enhance the dynamic tracking performance, a differential feedforward link is introduced between the desired speed and the output signal. The simulation and experimental results demonstrate that when the expected electrical angle inputs are sinusoidal and pulse signals, the incorporation of the feedforward link and the adjustment of parameters in the ADRC lead to improved position-tracking capabilities and greater adaptability to load disturbances.

A study and analysis of input output linearization control of permanent magnet synchronous motor based on fuzzy observer

A study and analysis of input output linearization control of permanent magnet synchronous motor based on fuzzy observer

Voltage Angle-Based Torque Control of Dual Three-Phase Interior Permanent Magnet Synchronous Motor Considering Mismatch in Winding Parameters

Voltage Angle-Based Torque Control of Dual Three-Phase Interior Permanent Magnet Synchronous Motor Considering Mismatch in Winding Parameters

High-Precision Sensorless Control of High-Speed Permanent Magnet Synchronous Motor Based on the Prediction Methodology

High-Precision Sensorless Control of High-Speed Permanent Magnet Synchronous Motor Based on the Prediction Methodology

Real-time advanced sensorless control of axial flux synchronous motor

Real-time advanced sensorless control of axial flux synchronous motor

Study of permanent magnet synchronous motor control based on sliding mode observer

Study of permanent magnet synchronous motor control based on sliding mode observer